Agents Reshape Their Search Strategy in Real Time, Unlock 25% Performance Gain

EvolveMem overturns a core assumption in RAG systems: that retrieval pipelines must remain frozen after deployment. By letting agents autonomously diagnose failures and adjust search parameters in real time, the system achieves 25% performance improvements on standard benchmarks. This shift from static to dynamic optimization offers production teams a concrete way to improve assistant performance without retraining models or expanding data.